Need for operational simplicity and timely disbursal of benefits-a qualitative exploration of the implementation of a direct benefit transfer scheme for persons with tuberculosis in India.

BACKGROUND: Ni-kshay Poshan Yojana (NPY) is a direct benefit transfer scheme of the Government of India introduced in 2018 to support the additional nutritional requirements of persons with TB (PwTB). Our recent nationwide evaluation of implementation and utilization of NPY using programmatic data of PwTB from nine randomly selected Indian states, reported a 70% coverage and high median delay in benefit credit. We undertook a qualitative study between January and July 2023, to understand the detailed implementation process of NPY and explore the enablers and barriers to effective implementation and utilization of the NPY scheme. METHODS: We followed a grounded theory approach to inductively develop theoretical explanations for social phenomena through data generated from multiple sources. We conducted 36 in-depth interviews of national, district and field-level staff of the National Tuberculosis Elimination Programme (NTEP) and NPY beneficiaries from 30 districts across nine states of India, selected using theoretical sampling. An analytical framework developed through inductive coding of a set of six interviews, guided the coding of the subsequent interviews. Categories and themes emerged through constant comparison and the data collection continued until theoretical saturation. RESULTS: Stakeholders perceived NPY as a beneficial initiative. Strong political commitment from the state administration, mainstreaming of NTEP work with the district public healthcare delivery system, availability of good geographic and internet connectivity and state-specific grievance redressal mechanisms and innovations were identified as enablers of implementation. However, the complex, multi-level benefit approval process, difficulties in accessing banking services, perceived inadequacy of benefits and overworked human resources in the NTEP were identified as barriers to implementation and utilization. CONCLUSION: The optimal utilization of NPY is enabled by strong political commitment and challenged by its lengthy implementation process and delayed disbursal of benefits. We recommend greater operational simplicity in NPY implementation, integrating NTEP activities with the public health system to reduce the burden on the program staff, and revising the benefit amount more equitably.

Direct benefit transfer for nutritional support of patients with TB in India-analysis of national TB program data of 3.7 million patients, 2018-2022.

BACKGROUND: Patients with TB have additional nutritional requirements and thus additional costs to the household. Ni-kshay Poshan Yojana(NPY) is a Direct Benefit Transfer (DBT) scheme under the National Tuberculosis Elimination Programme(NTEP) in India which offers INR 500 monthly to all notified patients with TB for nutritional support during the period of anti-TB treatment. Five years after its implementation, we conducted the first nationwide evaluation of NPY. METHODS: In our retrospective cohort study using programmatic data of patients notified with TB in nine randomly selected Indian states between 2018 and 2022, we estimated the proportion of patients who received at least one NPY instalment and the median time to receive the first instalment. We determined the factors associated (i) with non-receipt of NPY using a generalised linear model with Poisson family and log link and (ii) with time taken to receive first NPY benefit in 2022 using quantile regression at 50th percentile. RESULTS: Overall, 3,712,551 patients were notified between 2018 and 2022. During this period, the proportion who received at least one NPY instalment had increased from 56.9% to 76.1%. Non-receipt was significantly higher among patients notified by private sector (aRR 2.10;2.08,2.12), reactive for HIV (aRR 1.69;1.64,1.74) and with missing/undetermined diabetic status (aRR 2.02;1.98,2.05). The median(IQR) time to receive the first instalment had reduced from 200(109,331) days in 2018 to 91(51,149) days in 2022. Patients from private sector(106.9;106.3,107.4days), those with HIV-reactive (103.7;101.8,105.7days), DRTB(104.6;102.6,106.7days) and missing/undetermined diabetic status (115.3;114,116.6days) experienced longer delays. CONCLUSIONS: The coverage of NPY among patients with TB had increased and the time to receipt of benefit had halved in the past five years. Three-fourths of the patients received at least one NPY instalment, more than half of whom had waited over three months to receive the first instalment. NTEP has to focus on timely transfer of benefits to enable patients to meet their additional nutritional demands, experience treatment success and avoid catastrophic expenditure.

Quality of active case-finding for tuberculosis in India: a national level secondary data analysis.

BACKGROUND: India has been implementing active case-finding (ACF) for TB among marginalised and vulnerable (high-risk) populations since 2017. The effectiveness of ACF cycle(s) is dependent on the use of appropriate screening and diagnostic tools and meeting quality indicators. OBJECTIVES: To determine the number of ACF cycles implemented in 2021 at national, state (n = 36) and district (n = 768) level and quality indicators for the first ACF cycle. METHODS: In this descriptive study, aggregate TB program data for each ACF activity that was extracted was further aggregated against each ACF cycle at the district level in 2021. One ACF cycle was the period identified to cover all the high-risk populations in the district. Three TB ACF quality indicators were calculated: percentage population screened (≥10%), percentage tested among screened (≥4.8%) and percentage diagnosed among tested (≥5%). We also calculated the number needed to screen (NNS) for diagnosing one person with TB (≤1538). RESULTS: Of 768 TB districts, ACF data for 111 were not available. Of the remaining 657 districts, 642 (98%) implemented one, and 15 implemented two to three ACF cycles. None of the districts or states met all three TB ACF quality indicators' cut-offs. At the national level, for the first ACF cycle, 9.3% of the population were screened, 1% of the screened were tested and 3.7% of the tested were diagnosed. The NNS was 2824: acceptable (≤1538) in institutional facilities and poor for population-based groups. Data were not consistently available to calculate the percentage of i) high-risk population covered, ii) presumptive TB among screened and iii) tested among presumptive. CONCLUSION: In 2021, India implemented one ACF cycle with sub-optimal ACF quality indicators. Reducing the losses between screening and testing, improving data quality and sensitising stakeholders regarding the importance of meeting all ACF quality indicators are recommended.

Protocol for establishing a model for integrated influenza surveillance in Tamil Nadu, India.

The potential for influenza viruses to cause public health emergencies is great. The World Health Organisation (WHO) in 2005 concluded that the world was unprepared to respond to an influenza pandemic. Available surveillance guidelines for pandemic influenza lack the specificity that would enable many countries to establish operational surveillance plans. A well-designed epidemiological and virological surveillance is required to strengthen a country's capacity for seasonal, novel, and pandemic influenza detection and prevention. Here, we describe the protocol to establish a novel mechanism for influenza and SARS-CoV-2 surveillance in the four identified districts of Tamil Nadu, India. This project will be carried out as an implementation research. Each district will identify one medical college and two primary health centres (PHCs) as sentinel sites for collecting severe acute respiratory infections (SARI) and influenza like illness (ILI) related information, respectively. For virological testing, 15 ILI and 10 SARI cases will be sampled and tested for influenza A, influenza B, and SARS-CoV-2 every week. Situation analysis using the WHO situation analysis tool will be done to identify the gaps and needs in the existing surveillance systems. Training for staff involved in disease surveillance will be given periodically. To enhance the reporting of ILI/SARI for sentinel surveillance, trained project staff will collect information from all ILI/SARI patients attending the sentinel sites using pre-tested tools. Using time, place, and person analysis, alerts for abnormal increases in cases will be generated and communicated to health authorities to initiate response activities. Advanced epidemiological analysis will be used to model influenza trends over time. Integrating virological and epidemiological surveillance data with advanced analysis and timely communication can enhance local preparedness for public health emergencies. Good quality surveillance data will facilitate an understanding outbreak severity and disease seasonality. Real-time data will help provide early warning signals for prevention and control of influenza and COVID-19 outbreaks. The implementation strategies found to be effective in this project can be scaled up to other parts of the country for replication and integration.

A community-based study of dental fluorosis in rural children (6-12 years) from an aspirational district in Karnataka, India.

Objectives: The present study was planned to estimate the prevalence of dental fluorosis in 6-12 years of children and its association with various drinking water sources, water, and urine fluoride levels among the subset of children under the umbrella of a larger study to address iodine deficiency disorders and iron deficiency anemia in 17 villages of Manvi and Devadurga talukas of Raichur district of Karnataka. Methods: Analysis of subset of data and urine samples of children under the umbrella of a larger cross-sectional community-based study was conducted in 17 villages of Manvi and Devadurga taluks of Raichur district. House to house survey was carried out to collect data using a semi-structured questionnaire in ODK software. Demographic details, source of drinking water, clinical assessment of dental fluorosis, and height and weight measurements were performed by trained staff. Urine and water samples were collected for fluoride level estimation. The overall prevalence of dental fluorosis and its severity-wise prevalence were estimated. Association between dental fluorosis and age, gender, type of diet, source of drinking water, height for age, BMI for age, water fluoride level, and urine fluoride level were carried out using logistic regression analysis. Results: The prevalence of dental fluorosis was 46.0%. Mild, moderate, and severe dental fluorosis was found in 37.9, 7.8, and 0.3% of children. With the increasing age of participants, the odds of dental fluorosis were found to increase by 2-4 folds. The odds of having dental fluorosis were significantly increased with increasing water fluoride levels of 3 to 5 ppm [AOR = 3.147 (1.585-6.248); P = 0.001] in comparison with water fluoride levels of < 1 ppm. The similar trend was found with urine fluoride level > 4 ppm [AOR = 3.607 (1.861-6.990); P < 0.001]. As compared to river water, other sources of drinking water were significantly associated with higher odds of dental fluorosis. Conclusions: Prevalence of dental fluorosis was high in 6 to 12 years due to overexposure of fluoride from drinking water. High water and urine fluoride levels in children indicate the chronic exposure to fluoride and suggest that the population is at high risk of developing chronic fluorosis.

Burden of Typhoid and Paratyphoid Fever in India.

BACKGROUND: In 2017, more than half the cases of typhoid fever worldwide were projected to have occurred in India. In the absence of contemporary population-based data, it is unclear whether declining trends of hospitalization for typhoid in India reflect increased antibiotic treatment or a true reduction in infection. METHODS: From 2017 through 2020, we conducted weekly surveillance for acute febrile illness and measured the incidence of typhoid fever (as confirmed on blood culture) in a prospective cohort of children between the ages of 6 months and 14 years at three urban sites and one rural site in India. At an additional urban site and five rural sites, we combined blood-culture testing of hospitalized patients who had a fever with survey data regarding health care use to estimate incidence in the community. RESULTS: A total of 24,062 children who were enrolled in four cohorts contributed 46,959 child-years of observation. Among these children, 299 culture-confirmed typhoid cases were recorded, with an incidence per 100,000 child-years of 576 to 1173 cases in urban sites and 35 in rural Pune. The estimated incidence of typhoid fever from hospital surveillance ranged from 12 to 1622 cases per 100,000 child-years among children between the ages of 6 months and 14 years and from 108 to 970 cases per 100,000 person-years among those who were 15 years of age or older. Salmonella enterica serovar Paratyphi was isolated from 33 children, for an overall incidence of 68 cases per 100,000 child-years after adjustment for age. CONCLUSIONS: The incidence of typhoid fever in urban India remains high, with generally lower estimates of incidence in most rural areas. (Funded by the Bill and Melinda Gates Foundation; NSSEFI Clinical Trials Registry of India number, CTRI/2017/09/009719; ISRCTN registry number, ISRCTN72938224.).

Why should the men who have sex with men population in India be vigilant for monkeypox infection?

Monkeypox (MPX) is a zoonotic infection caused by the monkeypox virus (MPXV) and is primarily characterized by rash or pox marks and lymph node enlargement. The recent MPX has quickly spread across the globe and is now declared a global public health emergency. Being a contact illness, sexual encounters have been identified as the most common mode of transmission in the 2022 multicountry MPX outbreak. Data suggest that MPX is highly concentrated in men who have sex with men (MSM) networks and among those who had a recent sexual encounter with one or more partners. In India, the estimated MSM population was 569,346 in 2019. An analysis of the sexual partnerships among MSM suggests a potential highly interconnected MSM network in India, increasing the risk of MPX burden. The viewpoint emphasizes the need for community-level awareness and surveillance for the early detection and prevention of MPX infection in India.

Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus.

A complete sampling frame (CSF) is needed for the development of probability sampling structures; utilisation of a spatial sampling frame (SSF) was the objective of the present study. We used two sampling methods, simple random sampling (SRS) and stratified random sampling (STRS), to compare the prevalence estimates delivered by a CSF to that by a SSF when applied to self-reported hypertension and diabetes mellitus in a semi-urban setting and in a rural one. A CSF based on Geodatabase of all households and all individuals was available for our study that focused on adults aged 18-69 years in the two settings. A single digitized shapefile of solely household regions/structures as SSF was developed using Google Earth and employed for the study. The results from the two sampling frames were similar and not significantly different. All 95%CI calculations contained the prevalence rates of the two medical conditions except for one occasion based on STRS and CSF. The SRS based on CSF showed a minimum 95% CI width for diabetes mellitus, whereas SSF showed a minimum 95% CI width for hypertension. The coefficient of variation exceeded 10.0% on six occasions for CSF but only once for SSF, which was found to be as efficient as CSF.

Evaluating the effect of measles and rubella mass vaccination campaigns on seroprevalence in India: a before-and-after cross-sectional household serosurvey in four districts, 2018-2020.

BACKGROUND: India did phased measles-rubella supplementary immunisation activities (MR-SIAs; ie, mass-immunisation campaigns) targeting children aged 9 months to less than 15 years. We estimated measles-rubella seroprevalence before and after the MR-SIAs to quantify the effect on population immunity and identify remaining immunity gaps. METHODS: Between March 9, 2018 and March 19, 2020 we did community-based, cross-sectional serosurveys in four districts in India before and after MR-SIAs. 30 villages or wards were selected within each district, and one census enumeration block from each was selected as the survey cluster. Households were enumerated and 13 children in the younger age group (9 months to <5 years) and 13 children in the older ager group (5 to <15 years) were randomly selected by use of computer-generated random numbers. Serum samples were tested for IgG antibodies to measles and rubella viruses by enzyme immunoassay. FINDINGS: Specimens were collected from 2570 children before the MR-SIA and from 2619 children afterwards. The weighted MR-SIA coverage ranged from 73·7% to 90·5% in younger children and from 73·6% to 93·6% in older children. Before the MR-SIA, district-level measles seroprevalence was between 80·7% and 88·5% among younger children in all districts, and between 63·4% and 84·5% among older children. After the MR-SIA, measles seroprevalence among younger children increased to more than 90% (range 91·5 to 96·0) in all districts except Kanpur Nagar, in which it remained unchanged 80·4%. Among older children, measles seroprevalence increased to more than 90·0% (range 93·7% to 96·5%) in all districts except Hoshiarpur (88·7%). A significant increase in rubella seroprevalence was observed in all districts in both age groups, with the largest effect in Dibrugarh, where rubella seroprevalence increased from 10·6% to 96·5% among younger children. INTERPRETATION: Measles-rubella seroprevalence increased substantially after the MR-SIAs but the serosurvey also identified remaining gaps in population immunity. FUNDING: The Bill & Melinda Gates Foundation and Indian Council of Medical Research.

Development of the India COVID-19 vaccine tracker.

COVID-19 was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. Since then, efforts were initiated to develop safe and effective vaccines. Till date, 11 vaccines have been included in the WHO's emergency use list. The emergence and spread of variant strains of SARS-CoV-2 has altered the disease transmission dynamics, thus creating a need for continuously monitoring the real-world effectiveness of various vaccines and assessing their overall impact on disease control. To achieve this goal, the Indian Council of Medical Research (ICMR) along with the Ministry of Health and Family Welfare, Government of India, took the lead to develop the India COVID-19 Vaccination Tracker by synergizing three different public health databases: National COVID-19 testing database, CoWIN vaccination database and the COVID-19 India portal. A Vaccine Data Analytics Committee (VDAC) was constituted to advise on various modalities of the proposed tracker. The VDAC reviewed the data related to COVID-19 testing, vaccination and patient outcomes available in the three databases and selected relevant data points for inclusion in the tracker, following which databases were integrated, using common identifiers, wherever feasible. Multiple data filters were applied to retrieve information of all individuals ≥18 yr who died after the acquisition of COVID-19 infection with or without vaccination, irrespective of the time between vaccination and test positivity. Vaccine effectiveness (VE) against the reduction of mortality and hospitalizations was initially assessed. As compared to the hospitalization data, mortality reporting was found to be much better in terms of correctness and completeness. Therefore, hospitalization data were not considered for analysis and presentation in the vaccine tracker. The vaccine tracker thus depicts VE against mortality, calculated by a cohort approach using person-time analysis. Incidence of COVID-19 deaths among one- and two-dose vaccine recipients was compared with that among unvaccinated groups, to estimate the rate ratios (RRs). VE was estimated as 96.6 and 97.5 per cent, with one and two doses of the vaccines, respectively, during the period of reporting. The India COVID-19 Vaccination Tracker was officially launched on September 9, 2021. The high VE against mortality, as demonstrated by the tracker, has helped aid in allaying vaccine hesitancy, augmenting and maintaining the momentum of India's COVID-19 vaccination drive.

Clinical profile of patients infected with suspected SARS-CoV-2 Omicron variant of concern, Tamil Nadu, India, December 2021-January 2022.

Background & objectives: COVID-19 cases have been rising rapidly in countries where the SARS-CoV-2 variant of concern (VOC), Omicron (B.1.1.529) has been reported. We conducted a study to describe the epidemiological and clinical characteristics and outcomes of COVID-19 patients with 'S' gene target failure (SGTF, suspected Omicron). Furthermore, their clinical outcomes with COVID-19 patients with non-SGTF (non-Omicron) were also compared. Methods: This study was conducted in Tamil Nadu, India, between December 14, 2021 and January 7, 2022 among patients who underwent reverse transcription-PCR testing for SARS-CoV-2 in four laboratories with facilities for S gene screening. Consecutively selected COVID-19 patients with SGTF were telephonically contacted, seven and 14 days respectively after their date of positive result to collect information on the socio-demographic characteristics, previous history of COVID-19, vaccination status and clinical course of illness along with treatment details. To compare their outcomes with non-SGTF patients, one randomly suspected non-Omicron case for every two suspected Omicron cases from the line-list were selected, matching for the date of sample collection and the testing laboratory. Results: A total of 1175 SGTF COVID-19 patients were enrolled for this study. Almost 6 per cent (n=72) reported a history of previous infection. 141 (13.5%) suspected Omicron cases were non-vaccinated, while 148 (14.2%) and 703 (67.4%) had received valid one and two doses of COVID-19 vaccines, respectively. Predominant symptoms reported included fever (n=508, 43.2%), body pain (n=275, 23.4%), running nose (n=261, 22.2%) and cough (n=249, 21.2%). Five (0.4%) of the 1175 suspected Omicron cases required oxygen supplementation as compared to ten (1.6%) of the 634 suspected non-Omicron cases. No deaths were reported among omicron suspects, whereas there were four deaths among suspected non-Omicron cases. Interpretation & conclusions: Majority of the suspected Omicron cases had a mild course of illness. The overall severity of these cases was less compared to the suspected non-Omicron cases.

Seroprevalence of IgG antibodies against SARS-CoV-2 in India, March 2020 to August 2021: a systematic review and meta-analysis.

INTRODUCTION: India experienced 2 waves of COVID-19 pandemic caused by SARS-CoV-2 and reported the second highest caseload globally. Seroepidemiologic studies were done to track the course of the pandemic. We systematically reviewed and synthesized the seroprevalence of SARS-CoV-2 in the Indian population. METHODS: We included studies reporting seroprevalence of IgG antibodies against SARS-CoV-2 from March 1, 2020 to August 11, 2021 and excluded studies done only among patients with COVID-19 and vaccinated individuals. We searched published databases, preprint servers, and government documents using a combination of keywords and medical subheading (MeSH) terms of "Seroprevalence AND SARS-CoV-2 AND India". We assessed risk of bias using the Newcastle-Ottawa scale, the appraisal tool for cross-sectional studies (AXIS), the Joanna Briggs Institute (JBI) critical appraisal tool, and WHO's statement on the Reporting of Seroepidemiological Studies for SARS-CoV-2 (ROSES-S). We calculated pooled seroprevalence along with 95% Confidence Intervals (CI) during the first (March 2020 to February 2021) and second wave (March to August 2021). We also estimated seroprevalence by selected demographic characteristics. RESULTS: We identified 3821 studies and included 53 studies with 905379 participants after excluding duplicates, screening of titles and abstracts and full-text screening. Of the 53, 20 studies were of good quality. Some of the reviewed studies did not report adequate information on study methods (sampling = 24% (13/53); laboratory = 83% [44/53]). Studies of 'poor' quality had more than one of the following issues: unjustified sample size, nonrepresentative sample, nonclassification of nonrespondents, results unadjusted for demographics and methods insufficiently explained to enable replication. Overall pooled seroprevalence was 20.7% in the first (95% CI = 16.1 to 25.3) and 69.2% (95% CI = 64.5 to 73.8) in the second wave. Seroprevalence did not differ by age in first wave, whereas in the second, it increased with age. Seroprevalence was slightly higher among women in the second wave. In both the waves, the estimate was higher in urban than in rural areas. CONCLUSION: Seroprevalence increased by 3-fold between the 2 waves of the pandemic in India. Our review highlights the need for designing and reporting studies using standard protocols.

Seroprevalence of IgG antibodies against SARS-CoV-2 among the general population and healthcare workers in India, June-July 2021: A population-based cross-sectional study.

BACKGROUND: India began COVID-19 vaccination in January 2021, initially targeting healthcare and frontline workers. The vaccination strategy was expanded in a phased manner and currently covers all individuals aged 18 years and above. India experienced a severe second wave of COVID-19 during March-June 2021. We conducted a fourth nationwide serosurvey to estimate prevalence of SARS-CoV-2 antibodies in the general population aged ≥6 years and healthcare workers (HCWs). METHODS AND FINDINGS: We did a cross-sectional study between 14 June and 6 July 2021 in the same 70 districts across 20 states and 1 union territory where 3 previous rounds of serosurveys were conducted. From each district, 10 clusters (villages in rural areas and wards in urban areas) were selected by the probability proportional to population size method. From each district, a minimum of 400 individuals aged ≥6 years from the general population (40 individuals from each cluster) and 100 HCWs from the district public health facilities were included. The serum samples were tested for the presence of IgG antibodies against S1-RBD and nucleocapsid protein of SARS-CoV-2 using chemiluminescence immunoassay. We estimated the weighted and test-adjusted seroprevalence of IgG antibodies against SARS-CoV-2, along with 95% CIs, based on the presence of antibodies to S1-RBD and/or nucleocapsid protein. Of the 28,975 individuals who participated in the survey, 2,892 (10%) were aged 6-9 years, 5,798 (20%) were aged 10-17 years, and 20,285 (70%) were aged ≥18 years; 15,160 (52.3%) participants were female, and 21,794 (75.2%) resided in rural areas. The weighted and test-adjusted prevalence of IgG antibodies against S1-RBD and/or nucleocapsid protein among the general population aged ≥6 years was 67.6% (95% CI 66.4% to 68.7%). Seroprevalence increased with age (p < 0.001) and was not different in rural and urban areas (p = 0.822). Compared to unvaccinated adults (62.3%, 95% CI 60.9% to 63.7%), seroprevalence was significantly higher among individuals who had received 1 vaccine dose (81.0%, 95% CI 79.6% to 82.3%, p < 0.001) and 2 vaccine doses (89.8%, 95% CI 88.4% to 91.1%, p < 0.001). The seroprevalence of IgG antibodies among 7,252 HCWs was 85.2% (95% CI 83.5% to 86.7%). Important limitations of the study include the survey design, which was aimed to estimate seroprevalence at the national level and not at a sub-national level, and the non-participation of 19% of eligible individuals in the survey. CONCLUSIONS: Nearly two-thirds of individuals aged ≥6 years from the general population and 85% of HCWs had antibodies against SARS-CoV-2 by June-July 2021 in India. As one-third of the population is still seronegative, it is necessary to accelerate the coverage of COVID-19 vaccination among adults and continue adherence to non-pharmaceutical interventions.

Determinants of severity among hospitalised COVID-19 patients: Hospital-based case-control study, India, 2020.

BACKGROUND: Risk factors for the development of severe COVID-19 disease and death have been widely reported across several studies. Knowledge about the determinants of severe disease and mortality in the Indian context can guide early clinical management. METHODS: We conducted a hospital-based case control study across nine sites in India to identify the determinants of severe and critical COVID-19 disease. FINDINGS: We identified age above 60 years, duration before admission >5 days, chronic kidney disease, leucocytosis, prothrombin time > 14 sec, serum ferritin >250 ng/mL, d-dimer >0.5 ng/mL, pro-calcitonin >0.15 µg/L, fibrin degradation products >5 µg/mL, C-reactive protein >5 mg/L, lactate dehydrogenase >150 U/L, interleukin-6 >25 pg/mL, NLR ≥3, and deranged liver function, renal function and serum electrolytes as significant factors associated with severe COVID-19 disease. INTERPRETATION: We have identified a set of parameters that can help in characterising severe COVID-19 cases in India. These parameters are part of routinely available investigations within Indian hospital settings, both public and private. Study findings have the potential to inform clinical management protocols and identify patients at high risk of severe outcomes at an early stage.

Secondary attack rate of COVID-19 among contacts and risk factors, Tamil Nadu, March-May 2020: a retrospective cohort study.

OBJECTIVE: To describe the characteristics of contacts of patients with COVID-19 case in terms of time, place and person, to calculate the secondary attack rate (SAR) and factors associated with COVID-19 infection among contacts. DESIGN: A retrospective cohort study SETTING AND PARTICIPANTS: Contacts of cases identified by the health department from 14 March 2020to 30 May 2020, in 9 of 38 administrative districts of Tamil Nadu. Significant proportion of cases attended a religious congregation. OUTCOME MEASURE: Attack rate among the contacts and factors associated with COVID-19 positivity. RESULTS: We listed 15 702 contacts of 931 primary cases. Of the contacts, 89% (n: 14 002) were tested for COVID-19. The overall SAR was 4% (599/14 002), with higher among the household contacts (13%) than the community contacts (1%). SAR among the contacts of primary cases with congregation exposure were 5 times higher than the contacts of non-congregation primary cases (10% vs 2%). Being a household contact of a primary case with congregation exposure had a fourfold increased risk of getting COVID-19 (relative risk (RR): 16.4; 95% CI: 13 to 20) than contact of primary case without congregation exposure. Among the symptomatic primary cases, household contacts of congregation primaries had higher RR than household contacts of other cases ((RR: 25.3; 95% CI: 10.2 to 63) vs (RR: 14.6; 95% CI: 5.7 to 37.7)). Among asymptomatic primary case, RR was increased among household contacts (RR: 16.5; 95% CI: 13.2 to 20.7) of congregation primaries compared with others. CONCLUSION: Our study showed an increase in disease transmission among household contacts than community contacts. Also, symptomatic primary cases and primary cases with exposure to the congregation had more secondary cases than others.

Implementing Serosurveys in India: Experiences, Lessons Learned, and Recommendations.

Serological surveillance for vaccine-preventable diseases, such as measles and rubella, can provide direct measures of population immunity across age groups, identify gaps in immunity, and document changes in immunity over time. Rigorously conducted, representative household serosurveys provide high-quality estimates with minimal bias. However, they can be logistically challenging, expensive, and have higher refusal rates than vaccine coverage surveys. This article shares lessons learned through implementing nine measles and rubella household serosurveys in five districts in India-the challenges faced, the potential impact on results, and recommendations to facilitate the conduct of serosurveys. Specific lessons learned arose from challenges related to community mobilization owing to lack of cooperation in certain settings and populations, limitations of outdated census information, nonresponse due to refusal or unavailability during survey enumeration and enrollment, data collection issues, and specimen collection and handling issues. Although some experiences are specific to serosurveys in India, these lessons are generalizable to other household surveys, particularly vaccination coverage and serosurveys conducted in low- and middle-income settings.